Uma Grande Dica !!!
Title: Um Site sem divulgação é como Site sem divulgao como um Outdoor no poro de Casa !! Divulgue seu Site com seus produtos e serviços para milhões de compradores cadastrando-o em todos os Sites de Busca. Visite nosso Site para mais informações: www.idelco.com.br ou ligue (11) 5571.9699 *** Se você ainda não tem Site, nós podemos desenvolvê-lo *** Seu amigo(a) J.Oliveira que possui o e-mail [EMAIL PROTECTED] entrou em nosso Web-Site e enviou esta mensagem. Seu e-mail ou nome não estão gravados conosco. = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Pooled relative risks
Hi, Relative risk is commonly used in Epidemiology and Medical Statistics. It is simply the ratio of two proportions. Because of some desirable properties, it is usual to calculate instead of it another index, the *odds ratio*, that is a good approximation to relative risk in many practical cases, but not in all. I am concerned in the way of calculating pooled relative risks, since it is interesting in some *meta-analytical* applications. It is very easy to find formulas to obtain pooled odds ratios (the most known is Mantel-Haenszel's) but, up to now, I have not been able to find one for pooled relative risks. Could you help me with that? Thank you a lot. -- JFC = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: multivariate techniques for large datasets
In article 9g9k9f$h4c$[EMAIL PROTECTED], Eric Bohlman [EMAIL PROTECTED] wrote: In sci.stat.consult Tracey Continelli [EMAIL PROTECTED] wrote: value. I'm not sure why you'd want to reduce the size of the data set, since for the most part the larger the N the better. Actually, for datasets of the OP's size, the increase in power from the large size is a mixed blessing, for the same reason that many hard-of-hearing people don't terribly like wearing hearing aids: they bring up the background noise just as much as the signal. With an N of one million, practically *any* effect you can test for is going to be significant, regardless of how small it is. This just points out another stupidity of the use of significance testing. Since the null hypothesis is false anyhow, why should we care what happens to be the probability of rejecting when it is true? State the REAL problem, and attack this. -- This address is for information only. I do not claim that these views are those of the Statistics Department or of Purdue University. Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399 [EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558 = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Marijuana
There was some research recently linking heart attacks with Marijuana smoking. I'm trying to work out the correlation and, most importantly, its statistical significance. In essence the problem comes down to: Of 8760 hours in a year, 124 had heart attacks in them, 141 had MJ smokes in them and 9 had both. What statistical tests apply? Most importantly, what is the statistical significance of the correlation between smoking MJ in any hour and having a heart attack in that same hour? What is the probablity that the null hypothesis (that smoking marijuana and having a heart attack are unrelated) can be rejected? How reliable are the results from a dataset of this size? I'm not very literate in maths and stats - please help me out someone. I'm interested in this research from the perspective of medicinal marijuana. Thanks and take care, Paul All About MS - the latest MS News and Views http://www.mult-sclerosis.org/ = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: multivariate techniques for large datasets
On 13 Jun 2001 20:32:51 -0700, [EMAIL PROTECTED] (Tracey Continelli) wrote: Sidney Thomas [EMAIL PROTECTED] wrote in message news:[EMAIL PROTECTED]... srinivas wrote: Hi, I have a problem in identifying the right multivariate tools to handle datset of dimension 1,00,000*500. The problem is still complicated with lot of missing data. can anyone suggest a way out to reduce the data set and also to estimate the missing value. I need to know which clustering tool is appropriate for grouping the observations( based on 500 variables ). One of the best ways in which to handle missing data is to impute the mean for other cases with the selfsame value. If I'm doing psychological research and I am missing some values on my depression scale for certain individuals, I can look at their, say, locus of control reported and impute the mean value. Let's say [common finding] that I find a pattern - individuals with a high locus of control report low levels of depression, and I have a scale ranging from 1-100 listing locus of control. If I have a missing value for depression at level 75 for one case, I can take the mean depression level for all individuals at level 75 of locus of control and impute that for all missing cases in which 75 is the listed locus of control value. I'm not sure why you'd want to reduce the size of the data set, since for the most part the larger the N the better. Do you draw numeric limits for a variable, and for a person? Do you make sure, first, that there is not a pattern? That is -- Do you do something different depending on how many are missing? Say, estimate the value, if it is an oversight in filling blanks on a form, BUT drop a variable if more than 5% of responses are unexpectedly missing, since (obviously) there was something wrong in the conception of it, or the collection of it Psychological research (possibly) expects fewer missing than market research. As to the N - As I suggested before - my computer takes more time to read 50 megabytes than one megabyte. But a psychologist should understand that it is easier to look at and grasp and balance raw numbers that are only two or three digits, compared to 5 and 6. A COMMENT ABOUT HUGE DATA-BASES. And as a statistician, I keep noticing that HUGE databases tend to consist of aggregations. And these are random samples only in the sense that they are uncontrolled, and their structure is apt to be ignored. If you start to sample, to are more likely to ask yourself about the structure - by time, geography, what-have-you. An N of millions gives you tests that are wrong; estimates ignoring relevant structure have a spurious report of precision. To put it another way: the Error (or real variation) that *exists* between a fixed number of units (years, or cities, for what I mentioned above) is something that you want to generalize across. With a small N, that error term is (we assume?) small enough to ignore. However, that error term will not decrease with N, so with a large N, it will eventually dominate. The test based on N becomes increasing irrelevant -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Marijuana
David C. Ullrich wrote in message [EMAIL PROTECTED]... On Thu, 14 Jun 2001 15:22:25 +0100, Paul Jones [EMAIL PROTECTED] wrote: There was some research recently linking heart attacks with Marijuana smoking. I'm trying to work out the correlation and, most importantly, its statistical significance. In essence the problem comes down to: Of 8760 hours in a year, 124 had heart attacks in them, 141 had MJ smokes in them and 9 had both. What statistical tests apply? None. What you've said here makes no sense - what does it mean for an _hour_ to have MJ smoke? If you're actually reporting on actual research it would be interesting to know what the actual researchers actually said - if there's actual research out there that talks about the number of hours in a year containing smoke that will be remarkable. If otoh this is a homework question you should quote the question more accurately. (If the homework question _really_ reads _exactly_ the way you put it then you should complain to whoever assigned it that it makes no sense.) Most importantly, what is the statistical significance of the correlation between smoking MJ in any hour and having a heart attack in that same hour? Now this sounds more like you're talking about one person. This is an actual person who actually had 124 heart attacks in one year? I doubt it. What is the probablity that the null hypothesis (that smoking marijuana and having a heart attack are unrelated) can be rejected? How reliable are the results from a dataset of this size? I'm not very literate in maths and stats - please help me out someone. I'm interested in this research from the perspective of medicinal marijuana. Fascinating topic. If this is not actually homework you need to explain the question much more accurately. The data presented may refer to a much-reported study. (See, for example, http://www.eurekalert.org/releases/bidm-bsf022800.html ) To quote from there: The findings are the latest to emerge from a multicenter study of 3,882 patients who survived heart attacks. In this report, 124 people reported using marijuana regularly. Of these, 37 people reported using marijuana within 24 hours of their heart attacks, and nine smoked marijuana within an hour of their heart attacks. Note: 124 people... 9 within an hour... And 3882/37 + 37 = 141 MU = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Marijuana
Steve Leibel wrote: So the people who died from heart attacks weren't even considered in the study. Perhaps of all the people who had heart attacks, recent mj use was statistically correlated with saving their lives. That would be consistent with what you just described. So the methodology sounds bogus. That's not all - the MJ users had an excess of males, cigarette smokers and obese people - all increased risks for myocardial infarction. These articles rarely show statistical significance and it's hard to get hold of the full text without paying loads for it - besides, the full text might not quote p values. I want to know how statistically significant the association is, even given the studies obvious weaknesses. I need to know how to calculate a p value. If anyone could help it would be of great value to myself and a number of other PwMS. Thanks and take care, Paul All About MS - the latest MS News and Views http://www.mult-sclerosis.org/ = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Marijuana
In article 9galk6$fjr$[EMAIL PROTECTED], Mr Unreliable [EMAIL PROTECTED] wrote: David C. Ullrich wrote in message [EMAIL PROTECTED]... On Thu, 14 Jun 2001 15:22:25 +0100, Paul Jones [EMAIL PROTECTED] wrote: There was some research recently linking heart attacks with Marijuana smoking. I'm trying to work out the correlation and, most importantly, its statistical significance. In essence the problem comes down to: Of 8760 hours in a year, 124 had heart attacks in them, 141 had MJ smokes in them and 9 had both. What statistical tests apply? None. What you've said here makes no sense - what does it mean for an _hour_ to have MJ smoke? If you're actually reporting on actual research it would be interesting to know what the actual researchers actually said - if there's actual research out there that talks about the number of hours in a year containing smoke that will be remarkable. If otoh this is a homework question you should quote the question more accurately. (If the homework question _really_ reads _exactly_ the way you put it then you should complain to whoever assigned it that it makes no sense.) Most importantly, what is the statistical significance of the correlation between smoking MJ in any hour and having a heart attack in that same hour? Now this sounds more like you're talking about one person. This is an actual person who actually had 124 heart attacks in one year? I doubt it. What is the probablity that the null hypothesis (that smoking marijuana and having a heart attack are unrelated) can be rejected? How reliable are the results from a dataset of this size? I'm not very literate in maths and stats - please help me out someone. I'm interested in this research from the perspective of medicinal marijuana. Fascinating topic. If this is not actually homework you need to explain the question much more accurately. The data presented may refer to a much-reported study. (See, for example, http://www.eurekalert.org/releases/bidm-bsf022800.html ) To quote from there: The findings are the latest to emerge from a multicenter study of 3,882 patients who survived heart attacks. In this report, 124 people reported using marijuana regularly. Of these, 37 people reported using marijuana within 24 hours of their heart attacks, and nine smoked marijuana within an hour of their heart attacks. So the people who died from heart attacks weren't even considered in the study. Perhaps of all the people who had heart attacks, recent mj use was statistically correlated with saving their lives. That would be consistent with what you just described. So the methodology sounds bogus. = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Marijuana
David C. Ullrich wrote in message [EMAIL PROTECTED]... On Thu, 14 Jun 2001 15:22:25 +0100, Paul Jones [EMAIL PROTECTED] wrote: There was some research recently linking heart attacks with Marijuana smoking. I'm trying to work out the correlation and, most importantly, its statistical significance. In essence the problem comes down to: Of 8760 hours in a year, 124 had heart attacks in them, 141 had MJ smokes in them and 9 had both. What statistical tests apply? None. What you've said here makes no sense - what does it mean for an _hour_ to have MJ smoke? If you're actually reporting on actual research it would be interesting to know what the actual researchers actually said - if there's actual research out there that talks about the number of hours in a year containing smoke that will be remarkable. If otoh this is a homework question you should quote the question more accurately. (If the homework question _really_ reads _exactly_ the way you put it then you should complain to whoever assigned it that it makes no sense.) Most importantly, what is the statistical significance of the correlation between smoking MJ in any hour and having a heart attack in that same hour? Now this sounds more like you're talking about one person. This is an actual person who actually had 124 heart attacks in one year? I doubt it. What is the probablity that the null hypothesis (that smoking marijuana and having a heart attack are unrelated) can be rejected? How reliable are the results from a dataset of this size? I'm not very literate in maths and stats - please help me out someone. I'm interested in this research from the perspective of medicinal marijuana. Fascinating topic. If this is not actually homework you need to explain the question much more accurately. The data presented may refer to a much-reported study. (See, for example, http://www.eurekalert.org/releases/bidm-bsf022800.html ) To quote from there: The findings are the latest to emerge from a multicenter study of 3,882 patients who survived heart attacks. In this report, 124 people reported using marijuana regularly. Of these, 37 people reported using marijuana within 24 hours of their heart attacks, and nine smoked marijuana within an hour of their heart attacks. Note: 124 people... 9 within 24 hours... And 3882/37 + 37 = 141 MU = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Marijuana
Thanks for replying, David. I'll try to frame the problem better. First, I shall explain my motivations. There has recently been some research that implied that smoking MJ increased risk of heart attack in the hour following the heart attack. I haven't got the full text of the article - I've just seen the abstract, the press releases and resultant press coverage. There is a lot of dodgy research research and I want to know how statistically valid this research is. As you can imagine this topic is of great interest to people who use medicinal marijuana for multiple sclerosis as it has considerable benefit for neurogenic bladder problems, neuropathic pain and muscle spasms. The headline that MJ may increase heart attack risk in the hour following smoking it is extremely pertinent to people with MS. This explains my motives. This is not homework - I have MS. So the research says that of a large number of people who had heart attacks at a centre, 124 people had used MJ in the year preceding the HA. Of these 9 reported that they had used MJ in the hour preceding the HA. All MJ users were questioned on the frequency with which they used MJ. The relative risk was reported as 4.8 - I used this to back-calculate that the average number of MJ usages per year rounded 141 - (9/n)/(115/(8760-n)) = 4.8 I see an immediate mistake in what I wrote before - I have used the average Med MJ smokes but the total heart attacks. Restating the problem: Event A is smoking MJ. Event B is having HA. Let's assume that both events can only happen once per hour and that each person only had one HA. Of 1,086,240 hours, A happened 17,484 times, B happened 124 times and both A and B happened 9 times. What I want to know is what is the correlation between these two event? Most importantly, how statistically significant is the result? Can any reasonable conclusions be drawn from these data - esp, in view of the small dataset size? I would appreciate being corrected. Take care, Paul All About MS - the latest MS News and Views http://www.mult-sclerosis.org/ David C. Ullrich wrote: On Thu, 14 Jun 2001 15:22:25 +0100, Paul Jones [EMAIL PROTECTED] wrote: There was some research recently linking heart attacks with Marijuana smoking. I'm trying to work out the correlation and, most importantly, its statistical significance. In essence the problem comes down to: Of 8760 hours in a year, 124 had heart attacks in them, 141 had MJ smokes in them and 9 had both. What statistical tests apply? None. What you've said here makes no sense - what does it mean for an _hour_ to have MJ smoke? If you're actually reporting on actual research it would be interesting to know what the actual researchers actually said - if there's actual research out there that talks about the number of hours in a year containing smoke that will be remarkable. If otoh this is a homework question you should quote the question more accurately. (If the homework question _really_ reads _exactly_ the way you put it then you should complain to whoever assigned it that it makes no sense.) Most importantly, what is the statistical significance of the correlation between smoking MJ in any hour and having a heart attack in that same hour? Now this sounds more like you're talking about one person. This is an actual person who actually had 124 heart attacks in one year? I doubt it. What is the probablity that the null hypothesis (that smoking marijuana and having a heart attack are unrelated) can be rejected? How reliable are the results from a dataset of this size? I'm not very literate in maths and stats - please help me out someone. I'm interested in this research from the perspective of medicinal marijuana. Fascinating topic. If this is not actually homework you need to explain the question much more accurately. Thanks and take care, Paul All About MS - the latest MS News and Views http://www.mult-sclerosis.org/ David C. Ullrich * Sometimes you can have access violations all the time and the program still works. (Michael Caracena, comp.lang.pascal.delphi.misc 5/1/01) = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: multivariate techniques for large datasets
Herman Rubin wrote: In article 9g9k9f$h4c$[EMAIL PROTECTED], Eric Bohlman [EMAIL PROTECTED] wrote: In sci.stat.consult Tracey Continelli [EMAIL PROTECTED] wrote: value. I'm not sure why you'd want to reduce the size of the data set, since for the most part the larger the N the better. Actually, for datasets of the OP's size, the increase in power from the large size is a mixed blessing, for the same reason that many hard-of-hearing people don't terribly like wearing hearing aids: they bring up the background noise just as much as the signal. With an N of one million, practically *any* effect you can test for is going to be significant, regardless of how small it is. This just points out another stupidity of the use of significance testing. Since the null hypothesis is false anyhow, why should we care what happens to be the probability of rejecting when it is true? State the REAL problem, and attack this. How true! The only drawback there can be to more rather than less data for inferential purposes would have to center around the extra cost of computation, rather than the inconvenience posed to significance testing methodology. There is a significant philosophical question lurking here. It is a reminder of how we get so attached to the tools we use that we sometimes turn their bugs into features. Significance testing is a make-do construction of classical statistical inference, in some sense an indirect way of characterizing the uncertainty surrounding a parameter estimate. The Bayesian approach of attempting to characterize such uncertainty directly, rather than indirectly, and further of characterizing directly, through some function transformation of the parameter in question, the uncertainty surrounding some consequential loss or profit function critical to some real-world decision, is clearly laudable... if it can be justified. Clearly, from a classicist's perspective, the Bayesians have failed at this attempt at justification, otherwise one would have to be a masochist to stick with the sheer torture of classical inferential methods. Besides, the Bayesians indulge not a little in turning bugs into features themselves. At any rate, I say all that to say this: once it is recognized that there is a valid (extended) likelihood calculus, as easy of manipulation as the probability calculus in attempting a direct characterization of the uncertainty surrounding statistical model parameters, the gap between these two ought to be closed. I'm not holding my breath, as this may take several generations. We all reach for the tool we know how to use, not necessarily for the best tool for the job. Herman Rubin, Dept. of Statistics, Purdue Univ., West Lafayette IN47907-1399 [EMAIL PROTECTED] Phone: (765)494-6054 FAX: (765)494-0558 Regards, S. F. Thomas = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Marijuana
I was surprised to see this subject heading on sci.math. I thought it might have to do with the following lyrics (I forget the name of the group and the song): I smoke two joints at two o' clock; I smoke two joints at four. I smoke two joints before I smoke two joints, And then I smoke two more. Given an infinite supply of marijuana, even granting immortality to Cheech and Chong would not make the above feat possible. One would need to have existed for an infinite amout of time. And even then, smoking a joint takes at least one Planck time unit, so if you plot on a time-line the points at which each joint-pair- smoking finishes, there can't be any accumulation points. This would seem to preclude any such feat of pot-smoking . . . unless you somehow exist in a strange temporal topology (e.g., the long line). So then, how much marijuana would one have to smoke to actually change the nature of (one's personal) time in such a way? I'm guessing that no finite amount would suffice, but do not hazard a guess as to the precise cardnality required. | Jim Ferry | Center for Simulation | ++ of Advanced Rockets | | http://www.uiuc.edu/ph/www/jferry/ ++ |jferry@[delete_this]uiuc.edu| University of Illinois | = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Marijuana
On Thu, 14 Jun 2001 16:37:02 +0100, Mr Unreliable [EMAIL PROTECTED] wrote: David C. Ullrich wrote in message [EMAIL PROTECTED]... On Thu, 14 Jun 2001 15:22:25 +0100, Paul Jones [EMAIL PROTECTED] wrote: There was some research recently linking heart attacks with Marijuana smoking. [...] Fascinating topic. If this is not actually homework you need to explain the question much more accurately. The data presented may refer to a much-reported study. (See, for example, http://www.eurekalert.org/releases/bidm-bsf022800.html ) To quote from there: The findings are the latest to emerge from a multicenter study of 3,882 patients who survived heart attacks. In this report, 124 people reported using marijuana regularly. Of these, 37 people reported using marijuana within 24 hours of their heart attacks, and nine smoked marijuana within an hour of their heart attacks. Right. Seems to me (although I really know nothing about this sort of thing) that to draw any reliable conclusions (not that _you_'d care about that) we need to know a little more, like what fraction of the people who did _not_ get heart attacks smoke, regularly or otherwise. Note: 124 people... 9 within an hour... And 3882/37 + 37 = 141 MU David C. Ullrich * Sometimes you can have access violations all the time and the program still works. (Michael Caracena, comp.lang.pascal.delphi.misc 5/1/01) = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Marijuana
Brother! That topic sure drew a crowd! :) Paul Jones wrote: There was some research recently linking heart attacks with Marijuana smoking. [big snip] Jay -- Jay Warner Principal Scientist Warner Consulting, Inc. North Green Bay Road Racine, WI 53404-1216 USA Ph: (262) 634-9100 FAX: (262) 681-1133 email: [EMAIL PROTECTED] web: http://www.a2q.com The A2Q Method (tm) -- What do you want to improve today? = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
Re: Marijuana
Paul Jones wrote ... So the research says that of a large number of people who had heart attacks at a centre, 124 people had used MJ in the year preceding the HA. Of these 9 reported that they had used MJ in the hour preceding the HA. All MJ users were questioned on the frequency with which they used MJ. Keep in mind that correlation is not the same as causation. That's of particular importance in a study like this one. That is, if people are taking marijuana to treat pain and general discomfort, and if heart attacks are preceded by pain and discomfort, then there will be a strong correlation between marijuana use and later heart attacks, but it won't be proof of causation. = Instructions for joining and leaving this list and remarks about the problem of INAPPROPRIATE MESSAGES are available at http://jse.stat.ncsu.edu/ =
